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2023

Chao Lin, Ryozo Ooka, Hideki Kikumoto, Cédric Flageul, Youngseob Kim, Yunyi Wang, Alice Maison, Yang Zhang, Karine Sartelet, Large-eddy simulations on pollutant reduction effects of road-center hedge and solid barriers in an idealized street canyon, Building and Environment, 241, 2023, 110464, https://doi.org/10.1016/j.buildenv.2023.110464.

Dumont Le Brazidec, J., Bocquet, M., Saunier, O., and Roustan, Y.: Bayesian transdimensional inverse reconstruction of the Fukushima Daiichi caesium 137 release, Geosci. Model Dev., 16, 1039–1052, https://doi.org/10.5194/gmd-16-1039-2023, 2023.

Dumont Le Brazidec, J., Vanderbecken, P., Farchi, A., Bocquet, M., Lian, J., Broquet, G., Kuhlmann, G., Danjou, A., and Lauvaux, T.: Segmentation of XCO2 images with deep learning: application to synthetic plumes from cities and power plants, Geosci. Model Dev., 16, 3997–4016, https://doi.org/10.5194/gmd-16-3997-2023, 2023.

Farchi, A., Chrust, M., Bocquet, M., Laloyaux, P., & Bonavita, M. (2023). Online model error correction with neural networks in the incremental 4D-Var framework. Journal of Advances in Modeling Earth Systems, 15, e2022MS003474. https://doi.org/10.1029/2022MS003474

Finn, T. S., Durand, C., Farchi, A., Bocquet, M., Chen, Y., Carrassi, A., and Dansereau, V.: Deep learning subgrid-scale parametrisations for short-term forecasting of sea-ice dynamics with a Maxwell elasto-brittle rheology, The Cryosphere, 17, 2965–2991, https://doi.org/10.5194/tc-17-2965-2023, 2023.

Fiorentino E.-A., Chen H., Gandolfo A., Lannuque V., Sartelet K., Wortham H. (2023), Measurements and Modelling of OH and Peroxy Radicals in an Indoor Environment Under Different Light Conditions and VOC Levels. Atmos. Environ., 292, 119398, doi:10.1016/j.atmosenv.2022.119398.

Grudzien, C., & Bocquet, M. (2023). A Tutorial on Bayesian Data Assimilation. In A. Ismail-Zadeh, F. Castelli, D. Jones, & S. Sanchez (Eds.), Applications of Data Assimilation and Inverse Problems in the Earth Sciences (Special Publications of the International Union of Geodesy and Geophysics, pp. 27-48). Cambridge: Cambridge University Press. doi:10.1017/9781009180412.004

Lannuque, V., D'Anna, B., Kostenidou, E., Couvidat, F., Martinez-Valiente, A., Eichler, P., Wisthaler, A., Müller, M., Temime-Roussel, B., Valorso, R., and Sartelet, K.: Gas–particle partitioning of toluene oxidation products: an experimental and modeling study, Atmos. Chem. Phys., 23, 15537–15560, https://doi.org/10.5194/acp-23-15537-2023, 2023.

Lin, C., Wang, Y., Ooka, R., Flageul, C., Kim, Y., Kikumoto, H., Wang, Z., and Sartelet, K.: Modeling of street-scale pollutant dispersion by coupled simulation of chemical reaction, aerosol dynamics, and CFD, Atmos. Chem. Phys., 23, 1421–1436, https://doi.org/10.5194/acp-23-1421-2023, 2023.

M. Bocquet, “Surrogate modelling for the climate sciences dynamics with machine learning and data assimilation,” Front. Appl. Math. Stat., vol. 9, 2023, doi: 10.3389/fams.2023.1133226.

Vous souhaitez accéder à :

M. Bocquet, “Surrogate modelling for the climate sciences dynamics with machine learning and data assimilation,” Front. Appl. Math. Stat., vol. 9, 2023, doi: 10.3389/fams.2023.1133226.

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S. B. Cheng, C. Quilodrán-Casas, S. Ouala, A. Farchi, C. Liu, P. Tandeo, R. Fablet, D. Lucor, B. Iooss, J. Brajard, D. H. Xiao, T. Janjic, W. P. Ding, Y. K. Guo, A. Carrassi, M. Bocquet, and  R. Arcucci,  “Machine learning with data assimilation and uncertainty quantification for dynamical systems: A review,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 6, pp. 1361–1387, Jun. 2023. doi: 10.1109/JAS.2023.123537

Sarica, T., Maison, A., Roustan, Y., Ketzel, M., Jensen, S. S., Kim, Y., Chaillou, C., and Sartelet, K.: Modelling concentration heterogeneities in streets using the street-network model MUNICH, Geosci. Model Dev., 16, 5281–5303, https://doi.org/10.5194/gmd-16-5281-2023, 2023.

Thibaud Sarica, Karine Sartelet, Yelva Roustan, Youngseob Kim, Lya Lugon, Baptiste Marques, Barbara D'Anna, Christophe Chaillou, Clément Larrieu, Sensitivity of pollutant concentrations in urban streets to asphalt and traffic-related emissions, Environmental Pollution, 332, 121955, https://doi.org/10.1016/j.envpol.2023.121955, 2023

Vanderbecken, P. J., Dumont Le Brazidec, J., Farchi, A., Bocquet, M., Roustan, Y., Potier, É., and Broquet, G.: Accounting for meteorological biases in simulated plumes using smarter metrics, Atmos. Meas. Tech., 16, 1745–1766, https://doi.org/10.5194/amt-16-1745-2023, 2023.

Wang, T., Liu, H., Li, J., Wang, S., Kim, Y., Sun, Y., Yang, W., Du, H., Wang, Z., and Wang, Z.: A two-way coupled regional urban–street network air quality model system for Beijing, China, Geosci. Model Dev., 16, 5585–5599, https://doi.org/10.5194/gmd-16-5585-2023, 2023.

Wang, Z., Couvidat, F. and Sartelet, K. (2023), Implementation of a parallel reduction algorithm in the GENerator of reduced Organic Aerosol mechanisms (GENOA v2.0): Application to multiple monoterpene aerosol precursors, J. Aer. Sci., 174, 106248, doi:10.1016/j.jaerosci.2023.106248

Y. Wang, C. Flageul, A. Maison, B. Carissimo, and K. Sartelet, “Impact of trees on gas concentrations and condensables in a 2-D street canyon using CFD coupled to chemistry modeling,” Environmental Pollution, vol. 323, p. 121210, 2023, doi: https://doi.org/10.1016/j.envpol.2023.121210.